The ultimate goal in Huntington's disease (HD) is to develop disease-modifying therapies that will prevent the onset of clinical symptoms in those individuals who are at risk and slow the progression of symptoms in those individuals already affected with symptoms. Several neuroprotective strategies have been successful in transgenic models and hold potential for use in human studies. However, HD encompasses disordered motor control, cognition and emotion and the clinical heterogeneity and the unpredictable course of disease makes clinical trials in HD challenging. Indeed, it is difficult to find a signal that can be seen as preliminary evidence for activity or efficacy that would help the prioritization of compounds for large phase III studies. Moreover, while symptoms can be modulated pharmacologically, a symptomatic response may not correspond to disease modification or predict slowing of the disease process. Clinical trials testing potential neuroprotective treatments in symptomatic HD are currently based on insensitive and unreliable clinical outcome measures. Slowing of functional decline over time, a relatively insensitive but reliable measure, is the sine qua non of affecting progression and this requires following 100s of subjects for 2 to 5 years to detect a significant change. Markers of disease activity ("state") are urgently needed to facilitate early and late phase clinical trials. The inherent difficulties of performing clinical trials in slowly progressive neurodegenerative diseases are all the more challenging in the genetically at-risk population. Cognitive and emotional symptoms likely start more than a decade prior to the onset of motor dysfunction, and may be the greatest source of morbidity for individuals prior to a clinical diagnosis of HD. Several studies are currently focusing on developing cognitive assessments to detect early changes in this population;however, cognitive measures are highly variable in control populations and assessments of progressive changes in cognitive performance may lack the necessary sensitivity for interventional trials. Phenoconversion, the point at which an individuals presumably transitions from a state of "health" to one of illness is not a single point, but rather, represents that accumulation of multiple biological insults over time. Since HD is fundamentally a progressive neurodegenerative disease, a method for monitoring that neurodegeneration would be ideal. MRI morphometry holds great promise as a surrogate for progressive neurodegeneration as it can be used to prospectively measure brain shrinkage. Most efforts in HD so far have been focused on the striatum because it is so severely affected. However, by the time symptoms are detectable about 50% of the striatum has already atrophied such that there is already a floor effect reducing the sensitivity of the measures. We have found that MRI measures of cortical neurodegeneration are detectable years before symptom onset, are progressive in both presymptomatic and symptomatic HD, and correlate with disabling symptoms. More importantly, we have also found that in symptomatic HD, they appear to be responsive to neuroprotective treatments, and thus may have the potential to provide far greater experimental power than clinical outcomes. The principal goals of Project 1 are to determine the sensitivity, reliability and responsiveness of the MRI measures to treatment. However, we will not only compare MRI measures to clinical symptoms, we will also help examine how metabolomic (Project 2) and genomic (Project 3) biomarkers of HD correlate to our neuroimaging measures.